DCMS Economic Estimates: Productivity – Technical and quality assurance report

Question 1

1. Overview of release

Accepted Answer

The statistics release ‘DCMS Sector Economic Estimates: Productivity 2024’ reports on labour productivity for DCMS sectors. Labour productivity is defined as the economic output generated per unit of labour input.

In this publication, labour productivity is measured and presented using two separate metrics:

Output per hour worked: This is the preferred measure of productivity as it accounts for varying working patterns across industries. These estimates use Gross Value Added (GVA) as the output, with the total number of hours worked as the inputs.

Output per job: This metric has been reintroduced for the current release covering the 2019 to 2024 period. This measure was omitted from the previous publication due to temporary data unavailability. It uses GVA as the output and the total number of filled jobs as the input.

The estimates in this publication are designed to be consistent with national UK estimates published by the Office for National Statistics (ONS) where possible.

The scope of this release has been expanded to include productivity measures for both the civil society and tourism sectors. Additionally, a regional breakdown has been introduced for DCMS sectors, excluding civil society and tourism as regional GVA estimates are not available for these sectors.

1.1 Official statistics in development

These statistics are labelled as official statistics in development. Official statistics in development are official statistics that are undergoing development and will be tested with users, in line with the standards of trustworthiness, quality and value in the Code of Practice for Statistics. These productivity estimates are designed to complement our other economic estimates and to give a deeper understanding of the economic performance of DCMS sectors to the UK economy. They are being published as official statistics in development because:

they use data from the Annual Population Survey (APS) and the ONS productivity hours and productivity jobs series, which use the Labour Force Survey (LFS), among other data sources. The APS and LFS have been impacted by falling response rates and ONS has warned about the impact of these lower response rates on productivity data. Accreditation of ONS outputs based on these surveys has been suspended;
they include estimates for civil society and tourism for the first time;
they include regional estimates for the first time, and we will be further developing these to include a time series;
the methodology is still in development, including exploring the possibility of aligning estimates more closely with ONS productivity measures, potentially:
- incorporating jobs data from the Business Register and Employment Survey (BRES)
- using a component measure of productivity, in line with ONS ambitions to replace current estimates with a new measure using this approach;
we will be seeking user feedback on the usefulness of the statistics, the suitability of the methodology used and how clearly the statistics are communicated, including explanations about quality.

We expect to make further methodological improvements and implement changes after seeking user feedback. These changes will be made by the next annual productivity release, expected in 2027. At this point we will make an assessment about whether the statistics still remain in development or if the label can be removed.

We welcome feedback on these statistics. We particularly welcome views on:

the methodology and data sources used
the presentation of these measures and explanations about the quality of the data
suggestions for how these statistics could be further improved
how you are using the estimates

Please contact evidence@dcms.gov.uk by 25 September 2026 with any feedback.

1.2 Users

The users of these statistics fall into five broad categories:

Ministers and other political figures
Policy and other professionals in DCMS and other Government departments
Industries and their representative bodies
Charitable organisations
Academics

The primary use of these statistics is to monitor the performance of the industries in the DCMS sectors, helping to understand how current and future policy interventions can be most effective.

2.1 Overview of DCMS Sectors

2.1.1 Main sector definitions

These statistics cover the contributions of the following DCMS sectors to the UK economy:

civil society
creative industries
cultural sector
gambling
sport
tourism

In order to measure the size of the economy it is important to be able to define it. DCMS uses a range of definitions based on internal or UK agreed definitions. All definitions are based on the Standard Industrial Classification 2007 (SIC) codes. This means nationally consistent sources of data can be used and enables international comparisons.

Each sector definition has been designed to be the best possible measure of that individual sector. There are overlaps between DCMS sectors, whereby an industry (as defined by 4-digit Standard Industrial Classification, or SIC, codes) may be used in two sector definitions. In particular, the cultural sector is defined using SIC codes that are nearly all within the creative industries and the tourism industries and civil society overlap with other DCMS sectors. These overlaps are accounted for to avoid double counting in DCMS sector totals.

Figure 1 below visually shows the overlap between DCMS sectors in terms of SIC codes. Users should note that this does not give an indication of the magnitude of the value of overlap. For this, users should consult the main report. A list of SIC codes appearing in each sector and subsector can be found in the tables accompanying the release.

Figure 1: Overlap of SIC codes within DCMS Sectors

2.2 Details of sector definitions

This section looks at sector definitions in more detail.These sector definitions have been independently reviewed by the Office for Statistics Regulation (OSR) as part of their accreditation of a number of DCMS Sector Economic Estimates.

DCMS sector definitions are mostly based on the Standard Industrial Classification (SIC) framework which is used to classify business establishments and other statistical units by the type of economic activity in which they are engaged. The SIC system is internationally recognised, making it useful for comparisons across sectors, countries and over time. However, there are known limitations with the classification framework. As the balance and make-up of the economy changes, the SIC, finalised in 2007, is less able to provide the detail for important elements of the UK economy related to DCMS sectors.

The SIC codes used to produce DCMS sector definitions are a ‘best fit’, subject to the limitations described in the following section.

2.2.1 Creative industries

The creative industries were defined in the Government’s 2001 creative industries Mapping Document as “those industries which have their origin in individual creativity, skill and talent and which have a potential for wealth and job creation through the generation and exploitation of intellectual property”. Based on this definition, DCMS worked closely with stakeholders to determine which occupations and industries should be considered creative.

The creative industries were determined on the basis of creative intensity (the proportion of occupations in an industry that are creative), following the dynamic mapping process set out in a 2013 paper published by Nesta:

Through consultation, a list of creative occupations was identified.
The proportion of creative jobs in each industry was calculated (the creative intensity)
Industries with creative intensity above a specified threshold are considered creative industries

The definition is a UK definition based on internationally consistent industrial classifications which means estimates are comparable to the wider economy and useful internationally. The SIC codes used to capture the creative industries sector and sub-sectors are shown in the tables published alongside this guidance note. See the creative industries Economic Estimates methodology note for a more detailed explanation of how the definition has been derived.

2.2.2 Cultural sector

DCMS defines the cultural sector as those industries with a cultural object at the centre of the industry. DCMS proposed and consulted on a definition of the cultural sector in 2016, based on the availability of data through the SIC framework. There are limitations with the DCMS measurement of the cultural sector arising from the lack of detailed disaggregation possible using the standard industrial classifications. There are some cases where culture forms a small part of an industry classification and therefore cannot be separately identified and assigned as culture using standard data sources, this is particularly the case for the heritage sector.

It is recognised that, due to the limitations associated with SIC codes, the SIC code used in past publications as a proxy for the Heritage sector (91.03 - Operation of historical sites and building and similar visitor attractions) is likely to be an underestimate of this sector’s value. We have changed the name of the Heritage sector to ‘Operation for historical sites and similar visitor attractions’ to reflect this. We have been working on assessing methodologies for producing heritage sector economic estimates based on a broader definition which more accurately reflects the heritage sector. We are continuing to develop this methodology to produce robust heritage sector estimates.

2.2.3 Sport

For the purpose of this publication, the statistical definition of sport has been used based on the Vilnius definition. This incorporates only those 4-digit Standard Industrial Classification (SIC) codes which are predominantly sport (see the definitions in Table 1a in the published data tables).

DCMS also publishes some GVA and employment estimates based on the broad Vilnius definition as part of the DCMS Sport Satellite Account. This is a more wide-ranging measure of sport which considers the contribution of sport across a range of industries, for example sport advertising, and sport-related construction. However, this method has not been used in these estimates.

2.2.4 Tourism

Tourism is defined by the characteristics of the consumer in terms of whether they are a tourist or resident. This, therefore, differs from “traditional” industries such as gambling which are defined by the goods and services produced themselves, and means that a different approach to defining the industry is used.

For both GVA and jobs/hours, estimates for the tourism sector are based on a satellite account approach, which estimates the direct economic impact of tourism on the economy as a proportion of each individual industrial class - the tourism ratio. The tourism ratios are taken from the Office for National Statistics (ONS) Tourism Satellite Account (TSA) and TSA provisional indicator.

2.2.5 Civil society

The civil society sector covers non-market charities, voluntary organisations, trusts, social enterprises, mutuals, and community interest companies. Because it is defined by organizational structure and socio-economic purpose rather than an explicit type of industrial activity, it cannot be tracked using a standard list of business SIC codes.

Gross Value Added (GVA) : Civil society sector GVA expressed in current prices is based on NPISH (Non-profit institutions serving households) data. Non-profit institutions serving households are institutions that provide goods and services either for free or below the market prices, mainly derive their income from grants and donations, and are not controlled by the government. NPISH includes non-market charities, universities, trade unions and political parties. Of these, DCMS only covers the charity sector. NPISH does not include market provider charities who have passed the market test and therefore sit in the corporate sector (these data are not currently measured by ONS on a National Accounts basis), mutuals, social enterprises or community interest companies. It is therefore recognised that the published estimates are likely to be an underestimate for the civil society sector. In addition, because services are often provided free or at economically insignificant prices in the civil society sector, GVA does not capture all of the expected outputs.

Employment: Employment and labour inputs (jobs and hours worked) are estimated using microdata from the Annual Population Survey (APS) and the Labour Force Survey (LFS). Respondents report whether their primary or secondary employment is within a “private firm,” a “public sector body,” or a “voluntary organisation, charity, or trust.”

These differing definitions mean that productivity estimates for civil society are less robust than for other DCMS sectors.

2.2.6 Gambling

The definition of gambling used in DCMS sectors Economic Estimates is consistent with the internationally agreed definition, SIC 92 (‘Gambling and betting activities’).

Question 2

3. Methodology

Accepted Answer

3.1 Output per hour

Output per hour is the preferred measure of productivity as it accounts for different ways of working, for example, full-time and part-time working patterns.

3.1.1 Data sources

The following data sources were used to calculate output per hour for DCMS sectors:

3.1.2 Method (output per hour)

DCMS estimates of GVA from 2019 to 2023 and provisional estimates for 2024 are used as the output variable, ensuring consistency with the DCMS Sector Economic Estimates.

Current Price (CP) estimates provide level estimates for each calendar year in that year’s prices. Chained Volume Measures (CVM) are used to assess real growth between years by removing the effects of inflation.

The labour input is the total number of hours worked, estimated using ONS Annual Population Survey (APS) microdata. The survey records actual hours worked by respondents alongside self-reported SIC codes for both their first and second jobs. This microdata is weighted and aggregated to the 4-digit and 2-digit SIC levels to determine the ratio of hours worked within each 4-digit industry relative to its parent 2-digit industry division.

The ONS produces a productivity hours series at the industry division (2-digit SIC code) level. The 4-digit ratios calculated from the APS are applied to this ONS series to generate estimates at the 4-digit SIC level, which are then aggregated to produce DCMS sector and subsector totals.

Output per hour is calculated by dividing the sector or subsector GVA by the total constrained hours worked. This is performed for both CP GVA and CVM GVA series.

For smaller subsectors defined at a granular 4-digit SIC level, sample sizes within the APS can be small. This introduces higher statistical margins of error and artificial year-on-year volatility. Users should be cautious when interpreting changes over time for smaller sectors and subsectors, particularly short-term, single-year fluctuations.

3.2 Output per job

Output per job measures the average annual economic output associated with each filled job position. This series is reintroduced in this release, including data from 2019 to 2024.

3.2.1 Data sources

The data sources used to calculate output per job:

3.2.2 Method (output per job)

The output measure is the DCMS annual GVA CP and CVM series, as for output per hour.

The labour input is the number of filled jobs, derived from the APS microdata. The APS captures the count of main and second jobs held by survey respondents alongside self-reported SIC classifications. These job counts are weighted and aggregated to the 4-digit SIC level to establish the proportion of jobs within each 2-digit industry division.

These proportions are subsequently applied to the ONS productivity jobs series at the industry division (2-digit SIC) level. Output per job is calculated by dividing the sector or subsector GVA by the total constrained filled jobs.

3.3 Regional productivity

This publication includes UK regional productivity breakdowns for the first time.

DCMS sectors included in the regional estimates:

Creative industries
Cultural sector
Gambling
Sport

Regional productivity is not available for the civil society and tourism sectors, as regional GVA estimates are not available for these sectors.

Regional GVA

The DCMS regional GVA estimates used are taken from the most recent DCMS Economic Estimates: regional GVA 2023 publication.

Regional hours worked and jobs

The labour input is the number of filled jobs or actual hours worked, derived from the APS microdata. The APS captures the count of main and second jobs (and actual hours worked in these jobs) held by survey respondents alongside self-reported SIC classifications. These job/hours counts are weighted and aggregated to the 4-digit SIC level to establish the proportion of jobs within each 2-digit industry division. For regional data, this ratio calculation is also split by region of workplace, to obtain 4-digit SIC to 2-digit SIC ratios for each region of the UK.

These proportions are subsequently applied to the ONS productivity jobs and productivity hours series at the industry division (2-digit SIC) level, and geographically at the UK level.

Calculation of Regional Productivity

Regional output per hour and regional output per job are calculated by dividing regional GVA by the regionally apportioned hours or jobs for each sector.

In this publication, regional productivity estimates cover 2023 only, as regional GVA estimates are not currently available for 2024. This means that the GVA data used for regional estimates has not been revised following Blue Book 2025. We intend to publish updated regional estimates, including a time series from 2019 to 2024, when we publish regional GVA 2024, as data becomes available later in 2026.

3.4 Summary of data sources

In summary, the data presented in this report on productivity

are based on Official Statistics data sources
are based on internationally-harmonised codes
have been calculated to follow the ONS methodology as closely as possible
are based on survey data and, as with all data from surveys, there will be an associated error margin surrounding these estimates

This means the estimates are:

comparable at both a national and international level.

However, this also means the estimates are subject to limitations of the underlying classifications of the make-up of the UK economy. For example, the standard industrial classification (SIC) codes were developed in 2007 and have not been revised since. Emerging sectors, such as Artificial Intelligence, are therefore hard to capture and may be excluded or mis-coded.

3.5 Strengths and limitations

Strengths of these estimates

These estimates have been calculated to follow the ONS methodology as closely as possible, to aid comparability to UK national estimates.
The output measure used is the GVA published in the DCMS sector annual GVA publication, giving consistency across DCMS Economic Estimates.
Annual Population Survey data allows us to estimate actual hours worked, rather than usual or contracted hours.
Hours worked and jobs are constrained to the ONS productivity hours and jobs series. This enables us to use proportions of actual hours worked while keeping comparability to ONS data.

Limitations of these estimates

Several DCMS sectors’ outputs are not well represented by GVA alone (particularly in the cultural sector, for example, museums and libraries, and civil society). This is because these sectors’ goods and services are often provided free at the point of consumption. Also, GVA cannot capture wider cultural and societal benefits associated with these sectors (which may also include indirect effects on UK GVA). Hence, these productivity measures cannot fully account for output in these sectors. DCMS’s Cultural and Heritage Capital Programme sets out an ambition for a culture and heritage capital account that goes beyond transactions with market prices.
The underlying data for these estimates includes the Annual Population Survey (APS) estimates of hours worked and number of filled jobs in each 4-digit SIC code. While this enables us to estimate actual hours worked at a 4-digit SIC level, responses are self-reported, and SIC codes may therefore be less accurate. Due to ongoing challenges with response rates, response levels and weighting, the accreditation of ONS statistics based on the APS was temporarily suspended on 9 October 2024 and are considered official statistics in development until further review. As a result of the falling sample sizes, estimates based on the APS are likely to have increased volatility and uncertainty.
The ONS productivity jobs series and productivity hours series use the Labour Force Survey, which has experienced falling response rates and are therefore currently labelled as official statistics in development. This means there is greater uncertainty in DCMS sector estimates.
Regional estimates of productivity use the latest available regional GVA data, published before the publication of Blue Book 2025, and so do not take account of these revisions. They are therefore not comparable to the UK level productivity estimates, and will be updated when revised data becomes available later in 2026.

3.6 Changes in this release

In this release we have:

Reintroduced the output per job series, as the ONS productivity jobs series is available at SIC division level.
Introduced productivity estimates for the tourism and civil society sectors.
Introduced regional measures for DCMS sectors excluding tourism and civil society, for which regional GVA data is not available.

Question 3

4. Quality assurance processes

Accepted Answer

This chapter summarises the quality assurance processes applied during the production of the ‘DCMS Sectors Economic Estimates: Productivity 2024’ statistics. This includes an account of the quality assurance processes and data checks carried out by our data providers (ONS) as well as by DCMS.

4.1 Quality Assurance Processes at ONS

Quality assurance at ONS takes place at a number of stages. The various processes in place to ensure quality for the data sources used in the productivity publication are outlined below. Information presented here on the data sources is sourced from ONS technical documentation and is credited to colleagues at the ONS. Quality information on ONS measures of labour productivity overall are available in the ONS Labour Productivity Quality and Methodology Information (QMI) report.

4.1.2 Labour Force Survey (LFS) and Annual Population Survey (APS)

The Annual Population Survey (APS) is a continuous household survey, covering the UK. The topics covered include employment and unemployment, as well as housing, ethnicity, religion, health and education.

The purpose of the APS is to provide information on important social and socio-economic variables at local levels. The published statistics enable monitoring of estimates between censuses for a range of policy purposes and provide local area information for labour market estimates. The APS is not a stand-alone survey, but uses data combined from two waves of the main Labour Force Survey (LFS) with data collected on a local sample boost.

Labour Force Survey (LFS) estimates are subject to revisions generated by mid-year population estimates and every 10 years they are revised to census totals.

More details can be found in the ONS quality report.

4.1.3 DCMS Economic Estimates GVA 2024

For details of the methodology, data sources, and quality assurance processes in the production of DCMS sector GVA estimates, please refer to the DCMS Sectors Economic Estimates: GVA technical document, and the corresponding document for regional GVA.

4.2 Quality Assurance Processes at DCMS

The majority of quality assurance of the data underpinning the DCMS Sectors Economic Estimates: Productivity release takes place at ONS, as described above. However, further quality assurance checks are carried out within DCMS. Information about DCMS quality assurance of the DCMS sector GVA estimates is available in the corresponding technical report.

Production of the report is typically carried out by one member of staff, whilst quality assurance is completed by at least one other, to ensure an independent evaluation of the work.

4.2.1 Data requirements and data delivery

For the APS data, DCMS discussed our data requirements with ONS and these are formalised as a Data Access Agreement (DAA). The DAA covers which data are required, the purpose of the data, and the conditions under which ONS provide the data. Discussions of requirements and purpose with ONS improved the understanding of the data at DCMS, helping us to ensure we receive the correct data and use it appropriately.

DCMS checks that the data delivered by ONS match what is listed in the Data Access Agreement (DAA). For this particular release we check that:

We have received all data at the 4-digit SIC code level, which is required for us to aggregate up to produce estimates for our sectors and sub-sectors.
Data at the 4-digit SIC code has not been rounded unexpectedly. This would cause rounding errors when aggregating up to produce estimates for our sectors and subsectors.

4.2.2 Data Analysis quality assurance checks

At the analysis stage, data are aggregated to produce information about DCMS sectors and sub-sectors. The productivity statistics lead checks whether:

there is any missing data
the correct SIC codes have been aggregated together to form DCMS sector and sub-sector estimates

A statistics colleague not involved in the coding and analysis checks whether:

any new code or changes to code used in the calculations (in this case using the statistical software R) makes sense and produces the expected results
the correct input data is used (matching published data, incorporating any revisions, latest available data)
further calculations and analysis are correct.

4.2.3 Publication quality assurance checks

Finalised figures are disseminated within Excel tables and a written report published on GOV.UK. These are produced by the productivity statistics lead. Before publishing, a quality assurer checks the data tables as well as the report to ensure minimal errors. This is checked against a Quality Assurance (QA) log where comments can be fed back and actioned accordingly. The quality assurer also makes sure any statements made about the figures (e.g. regarding trends) are correct according to the analysis and checks for spelling or grammatical errors.

Proofreading and publication checks are done at the final stage, including:

checking the figures in the publication match the published tables
checking the footnote numbering is correct
making sure hyperlinks work
checking chart/table numbers are in the correct order
ensuring the publication is signed off by the DCMS Head of Profession for Statistics
contacting the press office to ensure they are aware of the release date
checking the published GOV.UK page again after publishing

4.2.4 Post publication

Once the publication is released, DCMS reviews the processes and procedures followed via a wash-up meeting. This occurs usually a week after the publication release date and discusses:

What went well and what issues were encountered
What improvements can be made for next time
Engaging with users of the publication to get feedback

Question 4

5. External Data Sources

Accepted Answer

It is recognised that there are always different ways to define sectors, but their relevance depends on what they are needed for. Government generally favours classification systems which are rigorously measured, internationally comparable, nationally consistent, and ideally applicable to specific policy interventions.

These are the main reasons for DCMS constructing sector classifications from Standard Industrial Classification (SIC) codes. However, DCMS accepts that there are limitations with this approach and alternative definitions can be useful where a policy-relevant grouping of businesses crosses existing Standard Industrial Classification (SIC) codes.

Question 5

6. Further information

Accepted Answer

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality, and value in the Code of Practice for Statistics that all producers of official statistics should adhere to. You are welcome to contact us directly with any comments about how we meet these standards. Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the Office for Statistics Regulation website.

For enquiries on this release, please email evidence@dcms.gov.uk.

For general enquiries, please see this guidance on how to contact the department.

For media enquiries, contact: 020 8080 3054

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